Target Discovery and Validation

Methods and Strategies for Drug Discovery

Alleyn T. Plowright, Raimund Mannhold, Helmut Buschmann, Jörg Holenz

• Publisher: Wiley-VCH
• Year: 2019
• Print ISBN: 9783527345298
• eBook ISBN: 9783527818266
• Edition: 1
• Topic: Medicine
• Subtopic: Pharmacology

The modern drug developers? guide for making informed choices among the diverse target identification methods

Target Discovery and Validation: Methods and Strategies for Drug Discovery offers a hands-on review of the modern technologies for drug target identification and validation. With contributions from noted industry and academic experts, the book addresses the most recent chemical, biological, and computational methods. Additionally, the book highlights techologies that are applicable to ?difficult? targets and drugs directed at multiple targets, including chemoproteomics, activity-based protein profiling, pathway mapping, genome-wide association studies, and array-based profiling.

Throughout, the authors highlight a range of diverse approaches, and target validation studies reveal how these methods can support academic and drug discovery scientists in their target discovery and validation research. This resource:

-Offers a guide to identifying and validating targets, a key enabling technology without which no new drug development is possible
-Presents the information needed for choosing the appropriate assay method from the ever-growing range of available options
-Provides practical examples from recent drug development projects, e. g. in kinase inhibitor profiling

Written for medicinal chemists, pharmaceutical professionals, biochemists, biotechnology professionals, and pharmaceutical chemists, Target Discovery and Validation explores the current methods for the identification and validation of drug targets in one comrpehensive volume. It also includes numerous practical examples.

1
Chemical Strategies for Evaluating New Drug Targets

Adrian J. Carter¹, Raina Seupel², Paul E. Brennan², Michael Sundström³, Andrea Introini³, and Anke Mueller‐Fahrnow⁴

¹ Boehringer Ingelheim, Discovery Research Coordination, Binger Strasse 173, 55216 Ingelheim, Germany

² University of Oxford, Structural Genomics Consortium and Target Discovery Institute, Nuffield Department of Medicine, NDMRB, Roosevelt Drive, Oxford, OX3 7FZ, UK

³ Karolinska Institutet, Structural Genomics Consortium, Karolinska Vägen 6, 17176, Sweden

⁴ Bayer AG, Target Discovery, Muellerstrasse 178, 13342 Berlin, Germany

1.1 Introduction

Discovering new drugs is difficult and expensive. Pharmaceutical companies typically spend at least $2.6 billion on average in research and development (R&D) for each drug before it reaches the market [1]. Interestingly, the high cost of R&D is not driven by the few programmes that succeed, but rather by the cost of pipeline projects that fail [2]. Only about 1 in 10 of drug candidates in phase I clinical trials actually makes it to become a new medicine [3,4], and about half of the projects that fail in phase II clinical trials do so because of clinical efficacy [5,6]. So why do so many drugs fail?

One answer is a lack of genetic evidence. An analysis of AstraZeneca's small molecule pipeline indicated that the success rate was over 70% for projects in phase II clinical trials with human genetic linkage of the target to the disease indication compared with 43% for projects without such a linkage [6]. Furthermore, another similar study concluded that selecting genetically supported targets can double the success rate in clinical development [7]. These observations have prompted some scientists to highlight the critical importance of the therapeutic hypothesis at the stage when a protein or gene is selected as a potential drug target [8]. However, it is often a long and difficult road between identifying a genetic link and understanding the underlying biological processes (see Chapter 6 for more details).

A major problem we are facing is that a large proportion of biomedical R&D focuses on only a small fraction of the genome despite the promised revolution in medicine following sequencing of the entire human genome [9]. Shortly after its announcement, scientists imagined that genome science would soon begin revealing the mysteries of hereditary factors in heart disease, cancer, diabetes, schizophrenia, and a host of other conditions and lead to new medicines [10]. Unfortunately, this has not happened. Indeed, more than 75% of protein research still focuses on the 10% of proteins that were known before the genome was mapped, even though many more have been genetically linked to disease [11]. A more recent analysis of drug targets highlights the continued dominance of a set of privileged target families across different disease areas, although there has also been a small growth of novel first‐in‐class mechanisms, particularly in oncology [12]. What can we do to help biomedical scientists worldwide to expand and prioritize the list of potential new drug targets?

One answer lies with high‐quality chemical probes. We know that chemical tools can dramatically facilitate exploratory biomedical research. Let us take, for example, nuclear hormone receptors. When nuclear receptors were identified by sequence homology in the 1990s, all the family members were thought to have therapeutic potential. Scientists initially investigated those receptors that were found to have genetic links to disease or that had interesting knockout phenotypes. However, as time went on, research activity focused on a subset of eight of these receptors despite the fact that these eight were no more genetically interesting than the others. Indeed Edwards [11] postulated that the only connection among these eight receptors is that for each there exists a widely available, high‐quality chemical probe that either enhances the receptor's activity or dampens it. In short, where high‐quality tools are available, there is research activity; where there are no tools, there is none. What is a high‐quality chemical probe and why are they so useful?

The Structural Genomics Consortium (SGC) (www.thesgc.org) is a large precompetitive public–private partnership between academia, private funders, and currently nine public pharmaceutical companies as well as patient advocacy and research organizations. The consortium has established a common set of principles for chemical probes, initially focused on epigenetic targets. A chemical probe is simply a small molecule that modulates the function of a protein in a specific and selective way. This allows a scientist to interrogate the biology and test hypotheses relating to the mechanism or role of the particular protein in a relevant cellular context [13]. The difference between specificity and selectivity is important to consider. Specificity is the capacity of a chemical probe to manifest only one kind of action. A chemical probe of perfect specificity of action might increase, or decrease, a specific function of a given cell type, but it would not do both, nor would it affect other receptors. In contrast, selectivity is the ability of a chemical probe to affect one cell population in preference to others, i.e. the ability of a chemical probe to affect one kind of cell, and produce effects, in doses lower than those required to affect other cells. This should not be confused with potency, i.e. the measure of the activity of a chemical probe, in terms of the concentration or amount...

Table of contents

• Cover
• Table of Contents
• Preface
• A Personal Foreword
• 1 Chemical Strategies for Evaluating New Drug Targets
• 2 Affinity‐Based Chemoproteomics for Target Identification
• 3 Activity‐Based Protein Profiling
• 4 Kinobeads: A Chemical Proteomic Approach for Kinase Inhibitor Selectivity Profiling and Target Discovery
• 5 Label‐Free Techniques for Target Discovery and Validation
• 6 Reverse Translation to Support Efficient Drug Target Selection and Stratified Medicine
• 7 Elucidating Target Biology and Drug Mechanism of Action Across Human Cell‐Based Model Systems
• 8 Cell Biology Methods in Target Validation
• 9 Genetic Manipulation/Modulation for Target Discovery and Validation
• 10 Computational Approaches for Target Inference
• 11 Bioinformatic Approaches in the Understanding of Mechanism of Action (MoA)
• Index
• End User License Agreement